{"uid":"cap_MF0nck3PowhMpQJN60IkP","slug":"expense-processing-duplicate-key-report-two-measure-correlation-38d54ebb","name":"Expense Processing — Duplicate Key Report + Two-Measure Correlation","description":"Expense processing — Duplicate key report + Two-measure correlation: Duplicate key report + Two-measure correlation for supplied expense processing records (submitted_amount, approved_amount). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-operations-07-066?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","team_group","date","submitted_amount","approved_amount"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"team_group":{"type":"string","default":"","maxLength":80},"approved_amount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"submitted_amount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","team_group":"group-a","approved_amount":1,"submitted_amount":10},{"date":"2026-10-02","row_id":"row-2","team_group":"group-b","approved_amount":2,"submitted_amount":20},{"date":"2026-10-03","row_id":"row-3","team_group":"group-a","approved_amount":3,"submitted_amount":15},{"date":"2026-10-04","row_id":"row-4","team_group":"group-b","approved_amount":4,"submitted_amount":30}],"maxItems":200,"minItems":1}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_yxoVRa2Eqdxv-KYdqNdcy","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Generates a duplicate key report and a two-measure Pearson/rank correlation analysis for expense records containing submitted_amount and approved_amount fields, using local analytical engines on up to 200 rows.","exampleAgentPrompt":"Can you run a duplicate key check and a correlation analysis between submitted_amount and approved_amount on my expense records? I have up to 50 rows with row_id, team_group, date, submitted_amount, and approved_amount — I want to see if any row IDs repeat and how strongly the two amounts are related.","exampleUseCases":[{"title":"Expense audit for duplicate submissions","prompt":"I have a batch of 120 expense rows from Q3 — each has a row_id, team_group, date, submitted_amount, and approved_amount. Can you check whether any row IDs are duplicated and also tell me how correlated the submitted and approved amounts are?"},{"title":"Finance team data quality check","prompt":"Our finance team submitted about 80 expense records and I need to verify there are no duplicate row IDs slipping through, and also see if there's a strong statistical correlation between what employees submitted versus what got approved."},{"title":"Cross-team expense pattern analysis","prompt":"I've got expense data from two team groups — group-a and group-b — with submitted and approved amounts for each row. Can you flag any duplicate keys and run a two-measure correlation so I can see if approvals track submissions consistently?"}],"resultDescription":"Returns two analytical reports: (1) a duplicate key report identifying any repeated row_id values across the submitted expense rows, and (2) a two-measure correlation report quantifying the statistical relationship between submitted_amount and approved_amount across up to 200 rows. No external lookups or predictions are performed; all analysis is local.","failureModes":["Empty rows array — rejected if fewer than 1 row provided","Exceeding 200 rows — input array truncated or rejected beyond maxItems limit","Invalid date format — rows with dates not matching YYYY-MM-DD pattern may be flagged or rejected","Missing required fields (row_id, submitted_amount, approved_amount) — validation error returned","Null numeric values in both measure columns — correlation may be undefined or return NaN","Non-unique row_id values treated as duplicates — expected behavior, not an error"],"whenToPreferThis":"Choose this endpoint when you need both a duplicate key audit and a two-measure correlation for expense data (submitted vs approved amounts) in a single $0.01 call covering up to 200 rows. Prefer this over general-purpose analytics tools when you need a lightweight, pre-packaged local analytical report without any external API dependencies, live lookups, or prediction models. Best suited for batch expense auditing, finance data quality checks, and detecting approval pattern anomalies.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T12:30:49.411Z","isFirstParty":false,"canonicalSlug":"expense-processing-duplicate-key-report-two-measure-correlation-38d54ebb"}